In this era of digitization, the media, broadcast, and e-commerce industries are recognizing the role of video-based information delivery methods as more effective as compared to other information sharing methods like text, audio, and images. The digitization has not only evolved media industries but has also nurtured the e-commerce and education industries as well. Nowadays, people are increasingly connected to real-time media, which is delivered in the form of audio podcasts and video streams. Apart from this, cheaper Internet services and inexpensive computing devices have enabled people to fetch and view on-demand video broadcasts and live video playbacks. For example, the YouTube™ video streaming platform alone has reported the streaming of four billion videos each day from around the world. In addition, over 65,000 new videos are uploaded every day on the YouTube™ platform which includes tutorials, how-to-do guides, music videos, movies, technology updates, promotions, and many other resources.
Further, video production houses have been relentlessly engaging to upgrade the in-premise technologies to facilitate the speedy editing, producing, and rendering of fresh or modified digital videos to impart comprehensive information along with the visual display. Accordingly, industries are exploring the latest technologies that can extract or embed context-sensitive information, metadata, and other geographical information in relation to videos. For example, a context-sensitive video may allow users to fetch varied information about any object rendered in the video by simply selecting the object with different input operations such as long tap, right-click, double-click, and hover. The context-sensitive video may be helpful to e-commerce industries for promoting their products while enabling the viewers to select desired objects from the video to fetch information about the selected objects. Moreover, educational institutions or universities can reap benefits from producing video-based learning courses having annotations and hyperlinks to each object rendered in the video to help students learn faster and better.
Generating video objects having dynamic context-sensitive information may be challenging these days as some of the current video editors have limited object extraction features like Magic Wand™ and Intelligent Scissors™ which can semi-automatically extract foregrounds from an image or video object. In addition, these prior video editing platforms are inefficient to facilitate video editing at minute pixel-by-pixel levels without altering the representation of the video. For example, in a 33 second video consisting of 825 frames where a video object is present in all frames, any type of method to embed context-sensitive metadata information associated with the video object would mean doing the same operation manually 825 times. The challenge is to have an efficient and minimalistic way of allowing the user to define interactive links for video objects within a video even when it is moving from frame to frame with shape changes and other transformations. Hence, there is a need for a platform to create intuitive video objects including context-sensitive metadata.